# 优化
from matplotlib import pyplot as plt
import numpy as np
import tensorflow as tf

def himmelblau(x):
    return (x[0]**2 + x[1] - 11)**2 + (x[0] + x[1]**2 - 7)**2


x = np.arange(-6, 6, 0.1)
y = np.arange(-6, 6, 0.1)
print('x,y,arange:', x.shape, y.shape)
X, Y = np.meshgrid(x, y)  # 生成坐标点
print('X,Y maps:', X.shape, Y.shape)
Z = himmelblau([X, Y])

fig = plt.figure("himmelblau")
ax = fig.gca(projection='3d')
ax.plot_surface(X, Y, Z)
ax.view_init(60, -30)
ax.set_xlabel('x')
ax.set_ylabel('y')
plt.show()

x = tf.constant([-4.,0.])

for step in range(200):

    with tf.GradientTape() as tape:
        tape.watch([x])
        y = himmelblau(x)
    
    grads = tape.gradient(y,[x])[0]
    x -= 0.01*grads

    if step % 20 == 0:
        print('step{}:x={},f(x)={}'.format(step,x.numpy(),y.numpy()))